import pandas as pd
import numpy as np
unemployment_2017 = pd.read_csv(r"C:\Users\JAJA\Documents\unemployment_2017.csv")
unemployment_2017.head()
| STATES | TOTAL UNEMPLOYED | UNEMPLOYMENT RATE | |
|---|---|---|---|
| 0 | Abia | 417,685 | 38.1 |
| 1 | Adamawa | 75,915 | 32.0 |
| 2 | Akwa Ibom | 903,733 | 45.6 |
| 3 | Anambra | 316,878 | 25.8 |
| 4 | Bauchi | 127,497 | 35.6 |
unemployment_2017.drop(index = 0,axis = 0,inplace = True)
unemployment_2017 = unemployment_2017.sort_values(by = "UNEMPLOYMENT RATE", ascending = False)
unemployment_2017.head()
| STATES | TOTAL UNEMPLOYED | UNEMPLOYMENT RATE | |
|---|---|---|---|
| 16 | Jigawa | 204,345 | 56.3 |
| 34 | Yobe | 165,380 | 51.7 |
| 31 | Rivers | 1,341,182 | 50.9 |
| 17 | Kaduna | 703,597 | 50.8 |
| 19 | Katsina | 41,038 | 46.9 |
unemployment_2017.dtypes
STATES object TOTAL UNEMPLOYED object UNEMPLOYMENT RATE float64 dtype: object
import plotly
import plotly.graph_objs as go
import plotly.express as px
import plotly.io as pio
fig = px.bar(unemployment_2017, y='STATES', x='UNEMPLOYMENT RATE', orientation='h', color='UNEMPLOYMENT RATE', text = 'UNEMPLOYMENT RATE')
fig.update_traces(texttemplate='%{text:.2s}%', textposition='outside')
fig.update_layout(uniformtext_minsize=8, uniformtext_mode='hide')
fig.update_layout(
title={
'text':"UNEMPLOYMENT RATE FOR THE YEAR 2017 Q1",
'y':0.95,
'x':0.5,
'xanchor': 'center',
'yanchor': 'top'},template = "plotly_white", height = 900, width = 1400)
import json
nigeria_states = json.load(open(r"C:\Users\JAJA\Documents\nigeria_geojson.json", "r"))
nigeria_states["features"][0]["properties"].keys()
dict_keys(['objectid', 'statecode', 'state', 'capcity', 'source', 'timestamp', 'globalid', 'shape_area', 'shape_len', 'geozone', 'cartodb_id', 'created_at', 'updated_at'])
state_id_map = {}
for feature in nigeria_states["features"]:
feature["id"] = feature["properties"]["statecode"]
state_id_map[feature["properties"]["state"]] = feature["id"]
unemployment_2017["id"] = unemployment_2017["STATES"].apply(lambda x: state_id_map[x])
fig = px.choropleth(unemployment_2017, geojson=nigeria_states, locations='id', color='UNEMPLOYMENT RATE',scope = "africa", hover_name = "STATES", hover_data = ["TOTAL UNEMPLOYED"])
fig.update_geos(fitbounds="locations", visible=False)
fig.show()